Data as of Aug 25, 2026 · Based on 283 AI responses · See how Parse measures this
AI Compute Infrastructure Solutions
Parse
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Google has risen to become the most cited provider for AI compute infrastructure between November 2025 and March 2026. While initially led discussions on performance and efficiency, responses have increasingly shifted to credit major cloud providers for delivering integrated, specialized AI hardware and confidential computing solutions.
| # | Brand | What AI says | Mention rate |
|---|---|---|---|
| 1 | 64% | ||
| 2 | Offers integrated confidential computing and federated learning infrastructure on Azure. | 60% | |
| 3 | Dominant for GPUs and provides the key FLARE framework for federated learning. | 55% | |
| 4 | A specialized leader in federated learning for biomedical and clinical research applications. | 54% | |
| 5 | 51% | ||
| 6 | 34% | ||
| 7 | 29% | ||
| 8 | 27% | ||
| 9 | 25% | ||
| 10 | 24% | ||
| 11 | 22% | ||
| 12 | 19% | ||
| 13 | A key hardware provider known for its SGX and TDX secure enclaves. | 18% | |
| 14 | 13% | ||
| 15 | 13% | ||
| 16 | 13% | ||
| 17 | 13% | ||
| 18 | 12% | ||
| 19 | 12% | ||
| 20 | 11% | ||
| 21 | 11% | ||
| 22 | 11% | ||
| 23 | 11% | ||
| 24 | 9% | ||
| 25 | 8% |
Who wins on each AI
The same market, seen by two models.
Sources AI cited
owkin.com is the page AI reaches for most here, cited in 55% of analyzed answers.
Dropped from #1 to #6 in overall citations between Nov 2025 and Mar 2026.
“The primary provider of energy-efficient hardware.” → “A key enabler of federated learning through its FLARE software framework.”
Emerged as a top infrastructure provider for federated learning in early 2026.
AWS Nitro Enclaves became a primary recommendation for secure AI inference by early 2026.
| Brand | ChatGPT Search | Google AI Mode | Comparison |
|---|---|---|---|
| 67% | 70% | ||
| 71% | 60% | ||
| 71% | 35% | ||
| 24% | 60% | ||
| 48% | 25% |
Google has risen to become the most cited provider for AI compute infrastructure between November 2025 and March 2026. While NVIDIA initially led discussions on performance and efficiency, responses have increasingly shifted to credit major cloud providers for delivering integrated, specialized AI hardware and confidential computing solutions.
Across 283 AI responses, Alphabet is mentioned most, named in 64% of them, followed by Microsoft (60%) and NVIDIA (55%).
Parse measures each brand's mention rate — the share of answers naming it — across 283 AI responses to this market's buyer questions. Answers are collected daily and the ranking is published weekly.
Brands enter the ranking when AI answers mention them. Parse collects answers daily and publishes the re-measured set weekly, so new brands appear as AI starts recommending them.
Responses consistently recommend solutions built on hardware TEEs like Intel SGX and
AMD SEV. Over the observado window, recommendations shifted from focusing on low-level hardware features towards integrated cloud offerings like
AWS Nitro Enclaves and Azure Confidential Computing, with specialized platforms like
also gaining prominence.
I need a secure enclave solution for running confidential AI inference.
Responses consistently recommend solutions built on hardware TEEs like Intel SGX and
AMD SEV. Over the observado window, recommendations shifted from focusing on low-level hardware features towards integrated cloud offerings like
AWS Nitro Enclaves and Azure Confidential Computing, with specialized platforms like also gaining prominence.
AI assistants initially focused heavily on hardware providers, with NVIDIA's GPUs consistently leading recommendations. By early 2026, responses broadened to include custom silicon from major cloud providers, such as 's TPUs and 's Trainium, framing energy efficiency as a full-stack challenge involving hardware, software, and data center cooling.
Brands mentioned
AI assistants initially focused heavily on hardware providers, with NVIDIA's GPUs consistently leading recommendations. By early 2026, responses broadened to include custom silicon from major cloud providers, such as
Google's TPUs and
Amazon's Trainium, framing energy efficiency as a full-stack challenge involving hardware, software, and data center cooling.